Data, as well as qualitative data for job

Data, a seemingly simple word that has influenced our lives
since humans existed over 200,000 years ago allowing us to analyse complex
situations and form reactions to them. Thousands of years ago, our ancestors
used data to survive, for example knowing what how to find safe shelter, or
what type of food would be safe to eat. Data used back then was small and
limited and all could be stored in our brains, however nowadays, the sheer
volume of data is immense, from financial data (revenue, profits or stock price)
to scientific data (information from lab experiments) as well as many other
types, to the extent where there will be 44 zettabytes by 20201 {reference 1}, which is equal to
44 trillion terabytes proving that data is absolutely vital. This essay will
discuss the basics of data, the uses of data from small to large scale, as well
as the drawbacks of data.

Data is
defined as ‘Facts and statistics collected together for reference or analysis,’
by the Oxford Dictionary {reference 2}, in other words, they can be pieces of
information that can be used for certain purposes. Data can be split into two
different categories; quantitative data and qualitative data. Quantitative data
is information measured in values expressed by numbers, wheras qualitative data
is information expressed non-numerically such as religion or gender. By using
both types of data, one can get the full picture of a population, for example finding
the quantitative data on income as well as qualitative data for job type for a
population can help you draw conclusions about what jobs pay certain incomes.

Data can be
stored as binary numbers, for example, letter can correspond to a number and
photographs can have an assigned number for brightness and colour of every
pixel. These are all represented by a string of 1’s and 0’s and this is mainly
stored in the hard disc drive of your computer. The Binary number can be
recorded using magnetism of either north or south however this can be influenced
using strong magnets that can corrupt the data being stored within. Modern
technology such as newer laptops uses solid state drive where the binary
numbers are recorded by the presence of charge in a series of tiny capacitors
in the chip. CDs use optics to store binary numbers. As the disk rotates, a
laser can either be reflected or not reflected by a series of tiny mirrored segments
on the disk. Empty discs can have a reflective layer that can be changed by the
laser in the computer.

Initially
data has to be collected first, for example by measurements, surveys or a large
scale, a census, which encompasses most people in a population and is carried
out every 10 years. After data is collected it is then analysed, which is the
process of evaluating data through inspection, cleansing, transforming and
modelling, using analytical and logical reasoning to examine each component of
the data provided. Data is useless if it cannot be analysed correctly as companies
wouldn’t be able to make vital decisions without the examination of the data
and it only becomes information that we can use after the analysis has
occurred. For example, if a factory is checking for faulty glass bottles by
counting the number of cracks, that data would need to be analysed in order for
a response to be created, whether investing in more reliable machinery if most bottles
are cracked or throwing away the bottles that are cracked. The data can then be
envisaged via graphs or photos making it easier to see trends or correlations
between data sets allowing you to see the full picture of a situation more
clearly.

Data is very
important in making judgements, which has resulted in companies making business
models centred around using ‘Big data.’ The phrase ‘Big data’ expresses the
massive increase in the amount of data collected and stored by organizations
around the world, with the total amount of data being captured and stored by
industries doubling every 1.2 years, showing the exponential increase in the
amount of data available to us.  Big Data
is best understood as an untapped resource that technology finally allows us to
exploit. For instance, data on weather, insects, and crop plantings has always
existed however it is now possible to cost-effectively collect those data and
use them in different ways.  ‘Facebook
stores, accesses, and analyses 30+ Petabytes of user generated data’. {reference3}.
Google processes and handles 200 petabytes of data per day this translates over
to 40,000 search queries every second, which is over 3.5 billion searches per
day and 1.2 trillion searches per year. {reference 4}. This large volume of
data available to large firms such as Facebook, twitter and google allow them
to understand their consumers for example from past data, what they usually
buy, what they might buy in the future, and companies can use this data to give
you adverts for products
and services one might be interested in. In this respect, google tailor’s
certain products to you. Google also offers services such as Google Analytics
to Google Big Query where companies can pay to access the plethora of data
available to find certain markets or trends within the data.

This data
has large economic benefits, In the US alone the ‘Big Data’ sector employs 11.6
million employees which is more than the entire population of Belgium. A report
from McKinsey Global Institute estimates that Big Data could generate an
additional $3 trillion in value every year in just seven industries across the
world, increasing the GDP in some developing countries and most developed countries
which have a strong IT sector. To add onto this companies that adopt
data-driven conclusions making achieve 5 to 6 percent higher productivity and
output growth than their competitors. This is vastly beneficial to the UK which
has a very poor productivity of workers with ‘Productivity no higher now than
it was just before the 2008 financial crisis.’ {reference 6}, and general
productivity 20% lower than before 2008.

Big Data has
benefits outside large businesses as well, it can tell you what is likely to happen,
through modelling certain situations using collected data, for example
determining how many people will visit a certain attraction depending on the
weather, which can then be prepared for by placing more workers at that
particular attraction. Big data can also prevent problems from occurring before
it becomes fatal. It can show the consequences of certain actions, for example
using sensors to collect data for a machine, it can tell when a part of the
machine is about to break and proceed to call in repairs as well as buy new
parts.

However big
data also has limitations. Although it can model the future to some degree, it
cannot predict the future with certainty. It can give you possibilities of what
is likely to occur however there is still a chance that it may not occur. In
addition, big data is enormous and there would be a battle to fetch relevant
information within all the data. Big data can also be misleading if the data
being collected is out-of-date or irrelevant to the actual investigation which
can lead to businesses being misguided. Bad analysis of the data can show
correlation between two data sets whereas they may have just been a random
coincidence. Finally, there is a large cost associated with Data collection,
aggregation, storage and analysis of data, which may not even help the company
using the data in the long run anyway.

Although
data is very significant, it has several weaknesses as well. There are several
privacy concerns with storing data online due to the ease of some companies
accessing your data, for example there has been a growing concern about who can
access personal information on the internet, as well as worries that your
emails may be stored and read by third parties. For example, some may not wish
medical records to be accessed by anyone as this could possibly lead to a
higher life insurance fee. Financially, data on prior transactions or credit
card numbers could be taken and used, also known as identity theft. This has
occurred several times such as in November 2017, a potential 40,000 customers
could have had their credit card data stolen from their OnePlus smartphone,
with many reporting credit card frauds. On a large scale ‘Over £1bn has been
stolen from bank accounts through credit and debit card fraud in the past 12
months,’ in the UK {Reference 7}, with an estimated 5 million people being a
victim of cybercrime. This clearly shows that there is a risk associated with
data with the possibility for your data to get into the wrong hands.

There are
laws in place regarding data and how it is handled. The Data Protection Act of 1998
aimed to protect personal data where individuals have the legal right to have
control of what information they give and what they want to withhold. This
means that the individual has to give consent for companies to use their
personal data if they are to abide by the law. Everyone responsible for using
data has to follow strict rules such as data must be kept for no longer than is
absolutely necessary, kept safe and secure and used in a way that is adequate,
relevant and not excessive. Generally, you can find out what information and
organisation has about you by asking for a copy and the firm is legally
required to had over that information. Poor protection of people’s information
led to Sony being hit by a £250,000 fine for failing to use up to date security
software affecting some 70
million gamers, compromising the personal information of millions of customers,
including their names, addresses, email addresses, dates of birth and account
passwords with Customers’ payment card details at risk as well.

Companies
are also at risk from getting hacked with five of the worst data thefts of all
time eBay, JP Morgan Chase, Adobe, Target, and Evernote carried out within the
last two years. This large-scale information hacking is becoming more prevalent
with personal information such as a billion Yahoo accounts being hacked in
2014. The larger the company is, the more likely that it as well as the
consumers using it would become a victim of data theft. Many of these threats
can be prevented by people by setting up firewalls or encrypting sensitive
files to prevent hackers from accessing them as well as set up antivirus
software on computers and phones that you want to protect. However larger
companies may have to invest more into security in order to maintain the trust
of their consumers and protect their information.

Overall, the
accumulation of data has revolutionised the world in the last few decades, and
has proved to be influential in every company’s operations. However, everyone
should know, this overdependence on data could lead to drawbacks which end up
doing more harm than good for the people as well as the company, through poor
security forcing companies such as Target to pay an $18.5 million settlement,
for a data breach that affected more than 41 million consumer payment card
accounts. More though needs to be put in so that large scale attacks such as
these do not happen as frequently as they are doing so. Despite the drawbacks,
data is vital for the quaternary sector providing millions of jobs as well as
beneficial growth for many countries. Companies such as Google may not even be
as dominant if data did not exist showing the clear impact that data has had on
us as a vital statistic and will continue to grow in size for the foreseeable
future.